{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Correlation, Distance, and Clustering performance of yeast sample-specific networks\n",
    "\n",
    "We check how well the clustering is done. We create two labels:\n",
    "- labels_genetics: same integer for samples with the same mutation (for instance all gcn4 together)\n",
    "- labels_media: same integer for samples in the same medium (for instance all YPD together)\n",
    "\n",
    "Then we apply rand scores, adjuster rand, mutual information"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**The files generate here are then used for the general comparisons shown in the manuscript**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import scipy.stats as stats\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "from sklearn.metrics import roc_auc_score, roc_curve\n",
    "\n",
    "def get_roc_correlation(correlation_matrix, sample, check = 'genetics'):\n",
    "    \"\"\" Compute roc curve and auc between the correlation values of a sample and the true values\n",
    "    The true labels are based on whether one wants to check the genetics or the media\n",
    "    For instance if one wants to check the roc for gcn4_ypd, the true labels are the genetics\n",
    "    the true labels are gonna be 1 only for the other gcn4 samples and 0 for the rest.\n",
    "    \n",
    "    Args:\n",
    "        correlation_matrix (pd.DataFrame): correlation matrix between all networks\n",
    "        sample (str): sample name, needs to correspond to the column name of the correlation matrix\n",
    "        check (str, optional): Either genetics or media. Defaults to 'genetics'.\n",
    "\n",
    "    Returns:\n",
    "        tpr, fpr, th, roc_auc\n",
    "    \"\"\"\n",
    "    \n",
    "    y_score = (correlation_matrix.loc[sample,[i for i in correlation_matrix.columns if i!= sample]]).values\n",
    "    if check == 'genetics':\n",
    "        group = sample.split('_')[0]\n",
    "        y_true = np.array([1 if i.split('_')[0] == sample.split('_')[0] else 0 for i in correlation_matrix.columns if i!= sample])\n",
    "    elif check == 'media':\n",
    "        group = sample.split('_')[1]\n",
    "        y_true = np.array([1 if i.split('_')[1] == sample.split('_')[1] else 0 for i in correlation_matrix.columns if i!= sample])\n",
    "    else:\n",
    "        print('Pass either genetics or media to check')\n",
    "        \n",
    "    tpr, fpr, th = roc_curve(y_true, y_score)\n",
    "    auc =  roc_auc_score(y_true, y_score)\n",
    "    \n",
    "    return tpr, fpr, th, auc, group\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Generic for clustering\n",
    "\n",
    "from sklearn.metrics import adjusted_rand_score, rand_score, mutual_info_score, adjusted_mutual_info_score, completeness_score, fowlkes_mallows_score, homogeneity_score, v_measure_score\n",
    "\n",
    "def get_clustering_scores(labels_media, labels_genetics, predicted_labels, method_label):\n",
    "    \"\"\"Get clustering scores (both for media and genetics) for a given clustering method.\n",
    "    This function computes the following scores: adjusted_rand_score, adjusted_mutual_info_score, \n",
    "    completeness_score, fowlkes_mallows_score, v_measure_score, homogeneity_score\n",
    "\n",
    "    Args:\n",
    "        labels_media (np.array): array of labels for media\n",
    "        labels_genetics (np.array): array of labels for genetics\n",
    "        predicted_labels (np.array): predictions of the clustering method\n",
    "        method_label (str): label of the clustering method\n",
    "    \"\"\"\n",
    "    df_clustering = pd.DataFrame(columns = ['metric', 'value', 'check'])\n",
    "    scores = [adjusted_rand_score, adjusted_mutual_info_score, completeness_score, fowlkes_mallows_score]\n",
    "\n",
    "    for i in scores:\n",
    "        s_media = i(labels_media, predicted_labels)\n",
    "        s_genetics = i(labels_genetics, predicted_labels)\n",
    "        \n",
    "        media_temp = pd.DataFrame({'metric': i.__name__, 'value': s_media, 'check':'media'}, index = [0])\n",
    "        genetics_temp = pd.DataFrame({'metric': i.__name__, 'value': s_genetics, 'check':'genetics'}, index = [0])\n",
    "        \n",
    "        df_clustering = pd.concat([df_clustering, media_temp, genetics_temp], axis = 0, ignore_index=True)\n",
    "        #df_clustering.append({'metric': i.__name__, 'value': s_media, 'check':'media'}, ignore_index = True)\n",
    "        #df_clustering = df_clustering.append({'metric': i.__name__, 'value': s_genetics, 'check':'genetics'}, ignore_index = True)\n",
    "\n",
    "    df_clustering['clustering_method'] = method_label\n",
    "    return(df_clustering)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_pdist_test(dist, sample, check = 'genetics', test = 'mw'):\n",
    "    \"\"\" Compute roc curve and auc between the correlation values of a sample and the true values\n",
    "    The true labels are based on whether one wants to check the genetics or the media\n",
    "    For instance if one wants to check the roc for gcn4_ypd, the true labels are the genetics\n",
    "    the true labels are gonna be 1 only for the other gcn4 samples and 0 for the rest.\n",
    "    \n",
    "    Args:\n",
    "        distance matrix (pd.DataFrame): correlation matrix between all networks\n",
    "        sample (str): sample name, needs to correspond to the column name of the correlation matrix\n",
    "        check (str, optional): Either genetics or media. Defaults to 'genetics'.\n",
    "\n",
    "    Returns:\n",
    "        tpr, fpr, th, roc_auc\n",
    "    \"\"\"\n",
    "    \n",
    "    if check == 'genetics':\n",
    "        group = sample.split('_')[0]\n",
    "        y_true = np.array([1 if i.split('_')[0] == sample.split('_')[0] else 0 for i in dist.columns])\n",
    "        y_true[network_dist.columns.tolist().index(sample)] = 0\n",
    "        y_false = np.array([1 if i.split('_')[0] != sample.split('_')[0] else 0 for i in dist.columns])\n",
    "    elif check == 'media':\n",
    "        group = sample.split('_')[1]\n",
    "        y_true = np.array([1 if i.split('_')[1] == sample.split('_')[1] else 0 for i in dist.columns])\n",
    "        y_true[network_dist.columns.tolist().index(sample)] = 0\n",
    "        y_false = np.array([1 if i.split('_')[1] != sample.split('_')[1] else 0 for i in dist.columns])\n",
    "    else:\n",
    "        print('Pass either genetics or media to check')\n",
    "    \n",
    "    a = dist.loc[sample,:].values[y_true==1]\n",
    "    b = dist.loc[sample,:].values[y_false==1]\n",
    "        \n",
    "    if test == 'mw':\n",
    "        res = scipy.stats.mannwhitneyu(a, b, use_continuity=True, alternative='less')\n",
    "    elif test == 'tt':\n",
    "        res = scipy.stats.ttest_ind(a, b, equal_var=True, alternative='less')\n",
    "    else:\n",
    "        print('test not recognized, choose mw or tt')\n",
    "    \n",
    "    return( res.statistic, res.pvalue, group)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.spatial.distance import pdist, squareform\n",
    "def get_distance_matrix(df, method = 'euclidean'):\n",
    "    \"\"\"Get distance matrix from a dataframe\n",
    "    Args:\n",
    "        df (pd.DataFrame): dataframe to compute the distance matrix\n",
    "        method (str, optional): method to compute the distance matrix. Defaults to 'pearson'.\n",
    "\n",
    "    Returns:\n",
    "        pd.DataFrame: distance matrix\n",
    "    \"\"\"\n",
    "    dist = pdist(df.values, method)\n",
    "    \n",
    "    return pd.DataFrame(squareform(dist), index = df.index, columns = df.index)\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read weights dataframe\n",
    "#with open('../data/processed/sweet/GSE125162_all_pseudobulk_logcounts_weight.txt', 'r') as f:\n",
    "#    weights = pd.read_csv(f, sep = '\\t')\n",
    "## weights.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# random edges\n",
    "#random_sweet = pd.read_csv('../data/processed/sweet/GSE125162_all_pseudobulk_logcounts_sweet_networks_1krandom.txt',sep = '\\t')\n",
    "#random_sweet.head()\n",
    "\n",
    "#random_sweet_clean = random_sweet#.iloc[:,2:]\n",
    "#random_sweet_clean.columns = [nets_fn[int(i.split('_')[-1])].split('/')[-1][:-4] if i.startswith('network') else i for i in random_sweet_clean.columns]\n",
    "#random_sweet_clean.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load the network\n",
    "\n",
    "Here we assume that one already has a file where each row is an edge and every column is a sample.\n",
    "Otherwise one can add a piece of code to generate this object.\n",
    "\n",
    "Here is a list of networks that we want to test:\n",
    "1. BONOBO sparse: bonobo edges sparsified\n",
    "2. BONOBO top1k: bonobo top 1k edges by mean value\n",
    "3. SWEET sparse: Edges sparsified by filtering SWEET Zscores\n",
    "4. SWEET top1k: SWEET top 1k edges by mean value\n",
    "5. LIONESS top 1k: LIONESS top 1K edges by mean value\n",
    "\n",
    "\n",
    "Change the folder and file names accordingly to the files of interest.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        vertical-align: middle;\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gene1</th>\n",
       "      <th>gene2</th>\n",
       "      <th>stp1_CStarve</th>\n",
       "      <th>rtg3_MinimalEtOH</th>\n",
       "      <th>gzf3_YPEtOH</th>\n",
       "      <th>gcn4_AmmoniumSulfate</th>\n",
       "      <th>dal81_MinimalEtOH</th>\n",
       "      <th>stp1_YPEtOH</th>\n",
       "      <th>rtg3_MinimalGlucose</th>\n",
       "      <th>rtg1_YPDRapa</th>\n",
       "      <th>...</th>\n",
       "      <th>stp2_YPD</th>\n",
       "      <th>dal81_Glutamine</th>\n",
       "      <th>rtg1_Urea</th>\n",
       "      <th>stp1_Glutamine</th>\n",
       "      <th>WT(ho)_MinimalGlucose</th>\n",
       "      <th>dal80_Urea</th>\n",
       "      <th>rtg1_MinimalGlucose</th>\n",
       "      <th>dal80_YPEtOH</th>\n",
       "      <th>dal82_MinimalGlucose</th>\n",
       "      <th>rtg3_AmmoniumSulfate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>YBL006W.A</td>\n",
       "      <td>YHL009W.A</td>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991912</td>\n",
       "      <td>...</td>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>YLR162W</td>\n",
       "      <td>YML090W</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>131.939063</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>...</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.991975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>YMR325W</td>\n",
       "      <td>YBL006W.A</td>\n",
       "      <td>0.934976</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>...</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.979498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>YDL034W</td>\n",
       "      <td>YKL224C</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>...</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>YDL246C</td>\n",
       "      <td>YDR344C</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>...</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.982613</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 134 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       gene1      gene2  stp1_CStarve  rtg3_MinimalEtOH  gzf3_YPEtOH  \\\n",
       "0  YBL006W.A  YHL009W.A      0.991912          0.991912     0.991912   \n",
       "1    YLR162W    YML090W      0.991975        131.939063     0.991975   \n",
       "2    YMR325W  YBL006W.A      0.934976          0.979498     0.979498   \n",
       "3    YDL034W    YKL224C      0.982991          0.982991     0.982991   \n",
       "4    YDL246C    YDR344C      0.982613          0.982613     0.982613   \n",
       "\n",
       "   gcn4_AmmoniumSulfate  dal81_MinimalEtOH  stp1_YPEtOH  rtg3_MinimalGlucose  \\\n",
       "0              0.991912           0.991912     0.991912             0.991912   \n",
       "1              0.991975           0.991975     0.991975             0.991975   \n",
       "2              0.979498           0.979498     0.979498             0.979498   \n",
       "3              0.982991           0.982991     0.982991             0.982991   \n",
       "4              0.982613           0.982613     0.982613             0.982613   \n",
       "\n",
       "   rtg1_YPDRapa  ...  stp2_YPD  dal81_Glutamine  rtg1_Urea  stp1_Glutamine  \\\n",
       "0      0.991912  ...  0.991912         0.991912   0.991912        0.991912   \n",
       "1      0.991975  ...  0.991975         0.991975   0.991975        0.991975   \n",
       "2      0.979498  ...  0.979498         0.979498   0.979498        0.979498   \n",
       "3      0.982991  ...  0.982991         0.982991   0.982991        0.982991   \n",
       "4      0.982613  ...  0.982613         0.982613   0.982613        0.982613   \n",
       "\n",
       "   WT(ho)_MinimalGlucose  dal80_Urea  rtg1_MinimalGlucose  dal80_YPEtOH  \\\n",
       "0               0.991912    0.991912             0.991912      0.991912   \n",
       "1               0.991975    0.991975             0.991975      0.991975   \n",
       "2               0.979498    0.979498             0.979498      0.979498   \n",
       "3               0.982991    0.982991             0.982991      0.982991   \n",
       "4               0.982613    0.982613             0.982613      0.982613   \n",
       "\n",
       "   dal82_MinimalGlucose  rtg3_AmmoniumSulfate  \n",
       "0              0.991912              0.991912  \n",
       "1              0.991975              0.991975  \n",
       "2              0.979498              0.979498  \n",
       "3              0.982991              0.982991  \n",
       "4              0.982613              0.982613  \n",
       "\n",
       "[5 rows x 134 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Choose network\n",
    "network_name = 'lioness_top1k'#'spcc_top1k'#'bonobo_sparse'#'bonobo_sparse'#'lioness_top1k'#'bonobo_sparse' #'sweet_top1k' \n",
    "results_folder = '../results/lioness_top1k_from20230908_20240209/'\n",
    "#'/Users/violafanfani/Documents/uni-harvard/projects/project-yeast-cycle-lioness/results/bonobo-yeast/sweet/sweet_top1k/'\n",
    "if os.path.isdir(results_folder) == False:\n",
    "    os.mkdir(results_folder)\n",
    "\n",
    "if network_name == 'sweet_sparse':\n",
    "    network = pd.read_csv('../data/processed/sweet/GSE125162_all_pseudobulk_logcounts_sweet_networks_sparse.txt', sep = '\\t')\n",
    "elif network_name == 'sweet_top1k': \n",
    "    network = pd.read_csv('../data/processed/sweet/GSE125162_all_pseudobulk_logcounts_sweet_networks_top1k.txt', sep = '\\t')\n",
    "elif network_name == 'bonobo_sparse': \n",
    "    network = pd.read_csv('inferelator/bonobo_sparse_from20230908_20240125/bonobo.csv')\n",
    "    #network = pd.read_csv('inferelator/bonobo_sparse_20240125/bonobo.csv') # This is done on 20231101 data\n",
    "elif network_name == 'bonobo_top1k': \n",
    "    network = pd.read_csv('inferelator/bonobo_top1k_from20230908_20240124/bonobo_top1k.csv')\n",
    "    #network = pd.read_csv('inferelator/bonobo_top1k_20240124/bonobo_top1k.csv')\n",
    "elif network_name == 'lioness_top1k': \n",
    "    network = pd.read_csv('../data/networks/lioness_top1k.csv')\n",
    "elif network_name == 'spcc_top1k':\n",
    "    network = pd.read_csv('spcc/networks/inferelator_spcc_top1k.csv')\n",
    "else:\n",
    "    sys.exit('Network (%s) not recognized' %network_name)\n",
    "network.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Correlation "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/envs/bonobo-env/lib/python3.9/site-packages/seaborn/matrix.py:560: UserWarning: Clustering large matrix with scipy. Installing `fastcluster` may give better performance.\n",
      "  warnings.warn(msg)\n",
      "/opt/conda/envs/bonobo-env/lib/python3.9/site-packages/seaborn/matrix.py:560: UserWarning: Clustering large matrix with scipy. Installing `fastcluster` may give better performance.\n",
      "  warnings.warn(msg)\n"
     ]
    },
    {
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",
      "text/plain": [
       "<Figure size 2000x2000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compute correlation matrix\n",
    "# we need to select the data only, removing the index values\n",
    "sns.set_context('paper')\n",
    "network_corr = network.iloc[:,2:].dropna(axis = 0).corr()\n",
    "g1 = sns.clustermap(network_corr, cmap = 'jet', xticklabels = False, yticklabels = 1, figsize = (20,20))\n",
    "g1.fig.savefig(results_folder + 'network_correlation.pdf', bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Compute ROC between Peearson and binary labels by both media and genetics\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_25687/3199061701.py:8: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
      "  corr_performance = pd.concat([corr_performance, df_temp], axis = 0)\n"
     ]
    }
   ],
   "source": [
    "# Let's check the individual networks and their correlation for genetics\n",
    "corr_performance = pd.DataFrame(columns = ['sample','auc', 'check', 'tpr', 'fpr', 'th', 'group'])\n",
    "for s in network.columns[2:]:\n",
    "    for ccc in ['genetics', 'media']:\n",
    "        tpr, fpr, th, auc, group = get_roc_correlation(network_corr, s, check = ccc)\n",
    "        # For each sample compute the ROC between the correlation values and the true values\n",
    "        df_temp = pd.DataFrame(data = [[s, auc, ccc, tpr, fpr, th, group]], columns = ['sample', 'auc', 'check', 'tpr', 'fpr', 'th', 'group'])\n",
    "        corr_performance = pd.concat([corr_performance, df_temp], axis = 0)\n",
    "\n",
    "corr_performance['network'] = network_name\n",
    "\n",
    "# Save network\n",
    "corr_performance.to_csv(results_folder + 'network_correlation_performance.csv', index = False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1120.25x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "media_color = '#d6604d'\n",
    "genetics_color = \"#4393c3\"\n",
    "\n",
    "sns.set_theme(style=\"whitegrid\")\n",
    "\n",
    "g1 = sns.catplot(data = corr_performance.sort_values(by = 'check'), x = 'group', y = 'auc', hue = 'check', \n",
    "                 kind = 'violin', \n",
    "                 aspect = 2, \n",
    "                 hue_order=['media', 'genetics'], palette = [media_color, genetics_color])\n",
    "# rotate xtick labels\n",
    "g1.set_xticklabels(rotation=90)\n",
    "# add horizontal grid lines\n",
    "g1.ax.yaxis.grid(True)\n",
    "# Add y axis line for 0.5\n",
    "g1.ax.axhline(0.5, ls = '--',lw= 2, color = 'red', alpha = 0.5)\n",
    "# Add title\n",
    "g1.ax.set_title(network_name)\n",
    "# Save figure\n",
    "g1.fig.savefig(results_folder + 'network_correlation_performance.pdf', bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "def make_pretty(styler):\n",
    "    styler.set_caption(\"Performance of the correlation between networks\")\n",
    "    #styler.format(rain_condition)\n",
    "    #styler.format_index(lambda v: v.strftime(\"%A\"))\n",
    "    styler.background_gradient(axis=None, vmin=-1, vmax=1, cmap=\"RdBu_r\")\n",
    "    return styler\n",
    "\n",
    "corr_performance.groupby(['check', 'group']).describe().iloc[:,1:].\\\n",
    "    style.pipe(make_pretty).\\\n",
    "    to_latex(results_folder + 'network_correlation_performance_describe.tex', convert_css=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Distance performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_25687/3347740435.py:13: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
      "  dist_performance = pd.concat([dist_performance, df_temp], axis = 0)\n"
     ]
    }
   ],
   "source": [
    "# Let's check the individual networks and their distance for genetics and media\n",
    "import scipy\n",
    "dist_performance = pd.DataFrame(columns = ['sample','test', 'check', 'stat', 'pval', 'group', 'method'])\n",
    "\n",
    "for method in ['euclidean', 'cosine']:\n",
    "    network_dist = get_distance_matrix(network.iloc[:,2:].dropna(axis = 0).T, method = method)\n",
    "    for s in network.columns[2:]:\n",
    "        for ccc in ['genetics', 'media']:\n",
    "            for test in ['mw']:\n",
    "                stat, p , group = get_pdist_test(network_dist, s, check = ccc, test = test)\n",
    "                # For each sample compute the ROC between the correlation values and the true values\n",
    "                df_temp = pd.DataFrame(data = [[s, test, ccc, stat, p,  group, method]], columns = ['sample','test', 'check', 'stat', 'pval', 'group', 'method'])\n",
    "                dist_performance = pd.concat([dist_performance, df_temp], axis = 0)\n",
    "\n",
    "\n",
    "dist_performance['network'] = network_name\n",
    "\n",
    "# Save network\n",
    "dist_performance.to_csv(results_folder + 'network_distance_performance.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sample</th>\n",
       "      <th>test</th>\n",
       "      <th>check</th>\n",
       "      <th>stat</th>\n",
       "      <th>pval</th>\n",
       "      <th>group</th>\n",
       "      <th>method</th>\n",
       "      <th>network</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>dal81_AmmoniumSulfate</td>\n",
       "      <td>mw</td>\n",
       "      <td>genetics</td>\n",
       "      <td>661.0</td>\n",
       "      <td>6.878386e-01</td>\n",
       "      <td>dal81</td>\n",
       "      <td>euclidean</td>\n",
       "      <td>spcc_top1k</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>dal81_AmmoniumSulfate</td>\n",
       "      <td>mw</td>\n",
       "      <td>media</td>\n",
       "      <td>343.0</td>\n",
       "      <td>4.312403e-03</td>\n",
       "      <td>AmmoniumSulfate</td>\n",
       "      <td>euclidean</td>\n",
       "      <td>spcc_top1k</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>dal81_CStarve</td>\n",
       "      <td>mw</td>\n",
       "      <td>genetics</td>\n",
       "      <td>677.0</td>\n",
       "      <td>7.351351e-01</td>\n",
       "      <td>dal81</td>\n",
       "      <td>euclidean</td>\n",
       "      <td>spcc_top1k</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>dal81_CStarve</td>\n",
       "      <td>mw</td>\n",
       "      <td>media</td>\n",
       "      <td>52.0</td>\n",
       "      <td>2.309036e-07</td>\n",
       "      <td>CStarve</td>\n",
       "      <td>euclidean</td>\n",
       "      <td>spcc_top1k</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>dal81_Glutamine</td>\n",
       "      <td>mw</td>\n",
       "      <td>genetics</td>\n",
       "      <td>637.0</td>\n",
       "      <td>6.109151e-01</td>\n",
       "      <td>dal81</td>\n",
       "      <td>euclidean</td>\n",
       "      <td>spcc_top1k</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gzf3_YPDDiauxic</td>\n",
       "      <td>mw</td>\n",
       "      <td>media</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.211450e-08</td>\n",
       "      <td>YPDDiauxic</td>\n",
       "      <td>cosine</td>\n",
       "      <td>spcc_top1k</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gzf3_YPDRapa</td>\n",
       "      <td>mw</td>\n",
       "      <td>genetics</td>\n",
       "      <td>636.0</td>\n",
       "      <td>6.075876e-01</td>\n",
       "      <td>gzf3</td>\n",
       "      <td>cosine</td>\n",
       "      <td>spcc_top1k</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gzf3_YPDRapa</td>\n",
       "      <td>mw</td>\n",
       "      <td>media</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.211450e-08</td>\n",
       "      <td>YPDRapa</td>\n",
       "      <td>cosine</td>\n",
       "      <td>spcc_top1k</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gzf3_YPEtOH</td>\n",
       "      <td>mw</td>\n",
       "      <td>genetics</td>\n",
       "      <td>701.0</td>\n",
       "      <td>7.985482e-01</td>\n",
       "      <td>gzf3</td>\n",
       "      <td>cosine</td>\n",
       "      <td>spcc_top1k</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gzf3_YPEtOH</td>\n",
       "      <td>mw</td>\n",
       "      <td>media</td>\n",
       "      <td>109.0</td>\n",
       "      <td>2.456088e-06</td>\n",
       "      <td>YPEtOH</td>\n",
       "      <td>cosine</td>\n",
       "      <td>spcc_top1k</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>528 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   sample test     check   stat          pval  \\\n",
       "0   dal81_AmmoniumSulfate   mw  genetics  661.0  6.878386e-01   \n",
       "0   dal81_AmmoniumSulfate   mw     media  343.0  4.312403e-03   \n",
       "0           dal81_CStarve   mw  genetics  677.0  7.351351e-01   \n",
       "0           dal81_CStarve   mw     media   52.0  2.309036e-07   \n",
       "0         dal81_Glutamine   mw  genetics  637.0  6.109151e-01   \n",
       "..                    ...  ...       ...    ...           ...   \n",
       "0         gzf3_YPDDiauxic   mw     media    0.0  2.211450e-08   \n",
       "0            gzf3_YPDRapa   mw  genetics  636.0  6.075876e-01   \n",
       "0            gzf3_YPDRapa   mw     media    0.0  2.211450e-08   \n",
       "0             gzf3_YPEtOH   mw  genetics  701.0  7.985482e-01   \n",
       "0             gzf3_YPEtOH   mw     media  109.0  2.456088e-06   \n",
       "\n",
       "              group     method     network  \n",
       "0             dal81  euclidean  spcc_top1k  \n",
       "0   AmmoniumSulfate  euclidean  spcc_top1k  \n",
       "0             dal81  euclidean  spcc_top1k  \n",
       "0           CStarve  euclidean  spcc_top1k  \n",
       "0             dal81  euclidean  spcc_top1k  \n",
       "..              ...        ...         ...  \n",
       "0        YPDDiauxic     cosine  spcc_top1k  \n",
       "0              gzf3     cosine  spcc_top1k  \n",
       "0           YPDRapa     cosine  spcc_top1k  \n",
       "0              gzf3     cosine  spcc_top1k  \n",
       "0            YPEtOH     cosine  spcc_top1k  \n",
       "\n",
       "[528 rows x 8 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dist_performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1120.25x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "media_color = '#d6604d'\n",
    "genetics_color = \"#4393c3\"\n",
    "\n",
    "sns.set_theme(style=\"whitegrid\")\n",
    "\n",
    "g1 = sns.catplot(data = dist_performance.sort_values(by = 'check'), y = 'group', x = 'stat', hue = 'check', \n",
    "                 kind = 'violin', \n",
    "                 aspect = 1, \n",
    "                 hue_order=['media', 'genetics'], palette = [media_color, genetics_color], \n",
    "                 col = 'method', \n",
    "                 row = 'test')\n",
    "\n",
    "# rotate xtick labels\n",
    "#g1.set_xticklabels(rotation=90)\n",
    "# add horizontal grid lines\n",
    "#g1.ax.yaxis.grid(True)\n",
    "# Add y axis line for 0.5\n",
    "#g1.ax.axhline(0.5, ls = '--',lw= 2, color = 'red', alpha = 0.5)\n",
    "g1.fig.savefig(results_folder + 'network_distance_performance.pdf', bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Clustering performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>YBL006W.A_YHL009W.A</th>\n",
       "      <th>YLR162W_YML090W</th>\n",
       "      <th>YMR325W_YBL006W.A</th>\n",
       "      <th>YDL034W_YKL224C</th>\n",
       "      <th>YDL246C_YDR344C</th>\n",
       "      <th>YMR325W_YHL009W.A</th>\n",
       "      <th>YLR264C.A_YHL048C.A</th>\n",
       "      <th>YDR112W_YHR086W.A</th>\n",
       "      <th>YBL006W.A_YJR162C</th>\n",
       "      <th>YPR159C.A_YBL006W.A</th>\n",
       "      <th>...</th>\n",
       "      <th>YLR110C_YBL075C</th>\n",
       "      <th>YMR118C_YKL096W.A</th>\n",
       "      <th>YDR524C.B_YMR118C</th>\n",
       "      <th>YDR524W.C_YBL006W.A</th>\n",
       "      <th>snR72_YBL006W.A</th>\n",
       "      <th>YLR044C_YMR175W</th>\n",
       "      <th>YLR110C_YHR139C</th>\n",
       "      <th>YKL106C.A_YER172C.A</th>\n",
       "      <th>YBL008W.A_YER172C.A</th>\n",
       "      <th>YLR110C_YMR118C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>stp1_CStarve</th>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.934976</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.924838</td>\n",
       "      <td>0.97995</td>\n",
       "      <td>0.97468</td>\n",
       "      <td>0.97095</td>\n",
       "      <td>0.519727</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.539511</td>\n",
       "      <td>-1.728102</td>\n",
       "      <td>-1.444611</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>-0.993298</td>\n",
       "      <td>-1.714633</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>-1.367036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rtg3_MinimalEtOH</th>\n",
       "      <td>0.991912</td>\n",
       "      <td>131.939063</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.973308</td>\n",
       "      <td>0.97995</td>\n",
       "      <td>0.97468</td>\n",
       "      <td>0.97095</td>\n",
       "      <td>0.969569</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.816487</td>\n",
       "      <td>-0.837744</td>\n",
       "      <td>-0.879595</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>-0.796037</td>\n",
       "      <td>-0.738971</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>-0.958905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gzf3_YPEtOH</th>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.973308</td>\n",
       "      <td>0.97995</td>\n",
       "      <td>0.97468</td>\n",
       "      <td>0.97095</td>\n",
       "      <td>0.969569</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.921459</td>\n",
       "      <td>-0.883231</td>\n",
       "      <td>-0.905551</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>-0.913164</td>\n",
       "      <td>-0.929638</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>-0.965489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gcn4_AmmoniumSulfate</th>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.973308</td>\n",
       "      <td>0.97995</td>\n",
       "      <td>0.97468</td>\n",
       "      <td>0.97095</td>\n",
       "      <td>0.969569</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.934689</td>\n",
       "      <td>-0.906175</td>\n",
       "      <td>-0.923734</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>-0.815117</td>\n",
       "      <td>-0.895104</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>-0.954177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dal81_MinimalEtOH</th>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.973308</td>\n",
       "      <td>0.97995</td>\n",
       "      <td>0.97468</td>\n",
       "      <td>0.97095</td>\n",
       "      <td>0.969569</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.903252</td>\n",
       "      <td>-0.605244</td>\n",
       "      <td>-0.865930</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>-0.983536</td>\n",
       "      <td>-0.920787</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>-0.931349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dal80_Urea</th>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.973308</td>\n",
       "      <td>0.97995</td>\n",
       "      <td>0.97468</td>\n",
       "      <td>0.97095</td>\n",
       "      <td>0.969569</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.926558</td>\n",
       "      <td>-0.913223</td>\n",
       "      <td>-0.860426</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>-0.962200</td>\n",
       "      <td>-0.902125</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>-0.957122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rtg1_MinimalGlucose</th>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.973308</td>\n",
       "      <td>0.97995</td>\n",
       "      <td>0.97468</td>\n",
       "      <td>0.97095</td>\n",
       "      <td>0.969569</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.929005</td>\n",
       "      <td>-0.926309</td>\n",
       "      <td>-0.933526</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>-0.946782</td>\n",
       "      <td>-0.927273</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>-0.967120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dal80_YPEtOH</th>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.973308</td>\n",
       "      <td>0.97995</td>\n",
       "      <td>0.97468</td>\n",
       "      <td>0.97095</td>\n",
       "      <td>0.969569</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.884394</td>\n",
       "      <td>-0.874747</td>\n",
       "      <td>-0.912958</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>-0.872898</td>\n",
       "      <td>-0.913120</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>-0.963707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dal82_MinimalGlucose</th>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.973308</td>\n",
       "      <td>0.97995</td>\n",
       "      <td>0.97468</td>\n",
       "      <td>0.97095</td>\n",
       "      <td>0.969569</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.898818</td>\n",
       "      <td>-0.906063</td>\n",
       "      <td>-0.907015</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>-0.932973</td>\n",
       "      <td>-0.868750</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>-0.936252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rtg3_AmmoniumSulfate</th>\n",
       "      <td>0.991912</td>\n",
       "      <td>0.991975</td>\n",
       "      <td>0.979498</td>\n",
       "      <td>0.982991</td>\n",
       "      <td>0.982613</td>\n",
       "      <td>0.973308</td>\n",
       "      <td>0.97995</td>\n",
       "      <td>0.97468</td>\n",
       "      <td>0.97095</td>\n",
       "      <td>0.969569</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.887107</td>\n",
       "      <td>-0.916240</td>\n",
       "      <td>-0.926957</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>0.042123</td>\n",
       "      <td>-0.861574</td>\n",
       "      <td>-0.924576</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>0.027097</td>\n",
       "      <td>-0.942690</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>132 rows × 1000 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      YBL006W.A_YHL009W.A  YLR162W_YML090W  YMR325W_YBL006W.A  \\\n",
       "stp1_CStarve                     0.991912         0.991975           0.934976   \n",
       "rtg3_MinimalEtOH                 0.991912       131.939063           0.979498   \n",
       "gzf3_YPEtOH                      0.991912         0.991975           0.979498   \n",
       "gcn4_AmmoniumSulfate             0.991912         0.991975           0.979498   \n",
       "dal81_MinimalEtOH                0.991912         0.991975           0.979498   \n",
       "...                                   ...              ...                ...   \n",
       "dal80_Urea                       0.991912         0.991975           0.979498   \n",
       "rtg1_MinimalGlucose              0.991912         0.991975           0.979498   \n",
       "dal80_YPEtOH                     0.991912         0.991975           0.979498   \n",
       "dal82_MinimalGlucose             0.991912         0.991975           0.979498   \n",
       "rtg3_AmmoniumSulfate             0.991912         0.991975           0.979498   \n",
       "\n",
       "                      YDL034W_YKL224C  YDL246C_YDR344C  YMR325W_YHL009W.A  \\\n",
       "stp1_CStarve                 0.982991         0.982613           0.924838   \n",
       "rtg3_MinimalEtOH             0.982991         0.982613           0.973308   \n",
       "gzf3_YPEtOH                  0.982991         0.982613           0.973308   \n",
       "gcn4_AmmoniumSulfate         0.982991         0.982613           0.973308   \n",
       "dal81_MinimalEtOH            0.982991         0.982613           0.973308   \n",
       "...                               ...              ...                ...   \n",
       "dal80_Urea                   0.982991         0.982613           0.973308   \n",
       "rtg1_MinimalGlucose          0.982991         0.982613           0.973308   \n",
       "dal80_YPEtOH                 0.982991         0.982613           0.973308   \n",
       "dal82_MinimalGlucose         0.982991         0.982613           0.973308   \n",
       "rtg3_AmmoniumSulfate         0.982991         0.982613           0.973308   \n",
       "\n",
       "                      YLR264C.A_YHL048C.A  YDR112W_YHR086W.A  \\\n",
       "stp1_CStarve                      0.97995            0.97468   \n",
       "rtg3_MinimalEtOH                  0.97995            0.97468   \n",
       "gzf3_YPEtOH                       0.97995            0.97468   \n",
       "gcn4_AmmoniumSulfate              0.97995            0.97468   \n",
       "dal81_MinimalEtOH                 0.97995            0.97468   \n",
       "...                                   ...                ...   \n",
       "dal80_Urea                        0.97995            0.97468   \n",
       "rtg1_MinimalGlucose               0.97995            0.97468   \n",
       "dal80_YPEtOH                      0.97995            0.97468   \n",
       "dal82_MinimalGlucose              0.97995            0.97468   \n",
       "rtg3_AmmoniumSulfate              0.97995            0.97468   \n",
       "\n",
       "                      YBL006W.A_YJR162C  YPR159C.A_YBL006W.A  ...  \\\n",
       "stp1_CStarve                    0.97095             0.519727  ...   \n",
       "rtg3_MinimalEtOH                0.97095             0.969569  ...   \n",
       "gzf3_YPEtOH                     0.97095             0.969569  ...   \n",
       "gcn4_AmmoniumSulfate            0.97095             0.969569  ...   \n",
       "dal81_MinimalEtOH               0.97095             0.969569  ...   \n",
       "...                                 ...                  ...  ...   \n",
       "dal80_Urea                      0.97095             0.969569  ...   \n",
       "rtg1_MinimalGlucose             0.97095             0.969569  ...   \n",
       "dal80_YPEtOH                    0.97095             0.969569  ...   \n",
       "dal82_MinimalGlucose            0.97095             0.969569  ...   \n",
       "rtg3_AmmoniumSulfate            0.97095             0.969569  ...   \n",
       "\n",
       "                      YLR110C_YBL075C  YMR118C_YKL096W.A  YDR524C.B_YMR118C  \\\n",
       "stp1_CStarve                -1.539511          -1.728102          -1.444611   \n",
       "rtg3_MinimalEtOH            -0.816487          -0.837744          -0.879595   \n",
       "gzf3_YPEtOH                 -0.921459          -0.883231          -0.905551   \n",
       "gcn4_AmmoniumSulfate        -0.934689          -0.906175          -0.923734   \n",
       "dal81_MinimalEtOH           -0.903252          -0.605244          -0.865930   \n",
       "...                               ...                ...                ...   \n",
       "dal80_Urea                  -0.926558          -0.913223          -0.860426   \n",
       "rtg1_MinimalGlucose         -0.929005          -0.926309          -0.933526   \n",
       "dal80_YPEtOH                -0.884394          -0.874747          -0.912958   \n",
       "dal82_MinimalGlucose        -0.898818          -0.906063          -0.907015   \n",
       "rtg3_AmmoniumSulfate        -0.887107          -0.916240          -0.926957   \n",
       "\n",
       "                      YDR524W.C_YBL006W.A  snR72_YBL006W.A  YLR044C_YMR175W  \\\n",
       "stp1_CStarve                     0.042123         0.042123        -0.993298   \n",
       "rtg3_MinimalEtOH                 0.042123         0.042123        -0.796037   \n",
       "gzf3_YPEtOH                      0.042123         0.042123        -0.913164   \n",
       "gcn4_AmmoniumSulfate             0.042123         0.042123        -0.815117   \n",
       "dal81_MinimalEtOH                0.042123         0.042123        -0.983536   \n",
       "...                                   ...              ...              ...   \n",
       "dal80_Urea                       0.042123         0.042123        -0.962200   \n",
       "rtg1_MinimalGlucose              0.042123         0.042123        -0.946782   \n",
       "dal80_YPEtOH                     0.042123         0.042123        -0.872898   \n",
       "dal82_MinimalGlucose             0.042123         0.042123        -0.932973   \n",
       "rtg3_AmmoniumSulfate             0.042123         0.042123        -0.861574   \n",
       "\n",
       "                      YLR110C_YHR139C  YKL106C.A_YER172C.A  \\\n",
       "stp1_CStarve                -1.714633             0.027097   \n",
       "rtg3_MinimalEtOH            -0.738971             0.027097   \n",
       "gzf3_YPEtOH                 -0.929638             0.027097   \n",
       "gcn4_AmmoniumSulfate        -0.895104             0.027097   \n",
       "dal81_MinimalEtOH           -0.920787             0.027097   \n",
       "...                               ...                  ...   \n",
       "dal80_Urea                  -0.902125             0.027097   \n",
       "rtg1_MinimalGlucose         -0.927273             0.027097   \n",
       "dal80_YPEtOH                -0.913120             0.027097   \n",
       "dal82_MinimalGlucose        -0.868750             0.027097   \n",
       "rtg3_AmmoniumSulfate        -0.924576             0.027097   \n",
       "\n",
       "                      YBL008W.A_YER172C.A  YLR110C_YMR118C  \n",
       "stp1_CStarve                     0.027097        -1.367036  \n",
       "rtg3_MinimalEtOH                 0.027097        -0.958905  \n",
       "gzf3_YPEtOH                      0.027097        -0.965489  \n",
       "gcn4_AmmoniumSulfate             0.027097        -0.954177  \n",
       "dal81_MinimalEtOH                0.027097        -0.931349  \n",
       "...                                   ...              ...  \n",
       "dal80_Urea                       0.027097        -0.957122  \n",
       "rtg1_MinimalGlucose              0.027097        -0.967120  \n",
       "dal80_YPEtOH                     0.027097        -0.963707  \n",
       "dal82_MinimalGlucose             0.027097        -0.936252  \n",
       "rtg3_AmmoniumSulfate             0.027097        -0.942690  \n",
       "\n",
       "[132 rows x 1000 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# First we need to get a dataframe with samples on rows and edges on columns\n",
    "\n",
    "network.index = network.gene1 + '_' + network.gene2\n",
    "df = network.fillna(0).iloc[:,2:].T\n",
    "#df = network.dropna(axis = 0 ).iloc[:,2:].T\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sample</th>\n",
       "      <th>genetics</th>\n",
       "      <th>media</th>\n",
       "      <th>label_genetics</th>\n",
       "      <th>label_media</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>stp1_CStarve</td>\n",
       "      <td>stp1</td>\n",
       "      <td>CStarve</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>rtg3_MinimalEtOH</td>\n",
       "      <td>rtg3</td>\n",
       "      <td>MinimalEtOH</td>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>gzf3_YPEtOH</td>\n",
       "      <td>gzf3</td>\n",
       "      <td>YPEtOH</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>gcn4_AmmoniumSulfate</td>\n",
       "      <td>gcn4</td>\n",
       "      <td>AmmoniumSulfate</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>dal81_MinimalEtOH</td>\n",
       "      <td>dal81</td>\n",
       "      <td>MinimalEtOH</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>dal80_Urea</td>\n",
       "      <td>dal80</td>\n",
       "      <td>Urea</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>rtg1_MinimalGlucose</td>\n",
       "      <td>rtg1</td>\n",
       "      <td>MinimalGlucose</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>dal80_YPEtOH</td>\n",
       "      <td>dal80</td>\n",
       "      <td>YPEtOH</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>dal82_MinimalGlucose</td>\n",
       "      <td>dal82</td>\n",
       "      <td>MinimalGlucose</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>rtg3_AmmoniumSulfate</td>\n",
       "      <td>rtg3</td>\n",
       "      <td>AmmoniumSulfate</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>132 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   sample genetics            media  label_genetics  \\\n",
       "0            stp1_CStarve     stp1          CStarve              10   \n",
       "1        rtg3_MinimalEtOH     rtg3      MinimalEtOH               9   \n",
       "2             gzf3_YPEtOH     gzf3           YPEtOH               7   \n",
       "3    gcn4_AmmoniumSulfate     gcn4  AmmoniumSulfate               5   \n",
       "4       dal81_MinimalEtOH    dal81      MinimalEtOH               2   \n",
       "..                    ...      ...              ...             ...   \n",
       "127            dal80_Urea    dal80             Urea               1   \n",
       "128   rtg1_MinimalGlucose     rtg1   MinimalGlucose               8   \n",
       "129          dal80_YPEtOH    dal80           YPEtOH               1   \n",
       "130  dal82_MinimalGlucose    dal82   MinimalGlucose               3   \n",
       "131  rtg3_AmmoniumSulfate     rtg3  AmmoniumSulfate               9   \n",
       "\n",
       "     label_media  \n",
       "0              1  \n",
       "1              3  \n",
       "2             10  \n",
       "3              0  \n",
       "4              3  \n",
       "..           ...  \n",
       "127            6  \n",
       "128            4  \n",
       "129           10  \n",
       "130            4  \n",
       "131            0  \n",
       "\n",
       "[132 rows x 5 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We need to get a dataframe with the labels for each sample\n",
    "# genetics labels are labels between 0 and 11 (12 total)\n",
    "# media labels are labels between 0 and 10 (11 total)\n",
    "\n",
    "df_labels = pd.DataFrame(data = [df.index.tolist(), df.index.str.split('_').str[0].tolist(), df.index.str.split('_').str[1].tolist()], index = ['sample', 'genetics', 'media']).T\n",
    "df_labels['label_genetics'] = df_labels['genetics'].map({i[1]: i[0] for i in (df_labels.groupby(['genetics']).count().reset_index().sort_values(by = 'sample', ascending = False).iloc[:,:1]).itertuples()})\n",
    "df_labels['label_media'] = df_labels['media'].map({i[1]: i[0] for i in (df_labels.groupby(['media']).count().reset_index().sort_values(by = 'sample', ascending = False).iloc[:,:1]).itertuples()})\n",
    "#df_labels = df_labels.sort_values(by = 'label_media').set_index('sample')\n",
    "df_labels\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Clustering and performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Select the number of clusters\n",
    "nc = 14"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sample</th>\n",
       "      <th>genetics</th>\n",
       "      <th>media</th>\n",
       "      <th>label_genetics</th>\n",
       "      <th>label_media</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>stp1_CStarve</td>\n",
       "      <td>stp1</td>\n",
       "      <td>CStarve</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>rtg3_MinimalEtOH</td>\n",
       "      <td>rtg3</td>\n",
       "      <td>MinimalEtOH</td>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>gzf3_YPEtOH</td>\n",
       "      <td>gzf3</td>\n",
       "      <td>YPEtOH</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>gcn4_AmmoniumSulfate</td>\n",
       "      <td>gcn4</td>\n",
       "      <td>AmmoniumSulfate</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>dal81_MinimalEtOH</td>\n",
       "      <td>dal81</td>\n",
       "      <td>MinimalEtOH</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>dal80_Urea</td>\n",
       "      <td>dal80</td>\n",
       "      <td>Urea</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>rtg1_MinimalGlucose</td>\n",
       "      <td>rtg1</td>\n",
       "      <td>MinimalGlucose</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>dal80_YPEtOH</td>\n",
       "      <td>dal80</td>\n",
       "      <td>YPEtOH</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>dal82_MinimalGlucose</td>\n",
       "      <td>dal82</td>\n",
       "      <td>MinimalGlucose</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>rtg3_AmmoniumSulfate</td>\n",
       "      <td>rtg3</td>\n",
       "      <td>AmmoniumSulfate</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>132 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   sample genetics            media  label_genetics  \\\n",
       "0            stp1_CStarve     stp1          CStarve              10   \n",
       "1        rtg3_MinimalEtOH     rtg3      MinimalEtOH               9   \n",
       "2             gzf3_YPEtOH     gzf3           YPEtOH               7   \n",
       "3    gcn4_AmmoniumSulfate     gcn4  AmmoniumSulfate               5   \n",
       "4       dal81_MinimalEtOH    dal81      MinimalEtOH               2   \n",
       "..                    ...      ...              ...             ...   \n",
       "127            dal80_Urea    dal80             Urea               1   \n",
       "128   rtg1_MinimalGlucose     rtg1   MinimalGlucose               8   \n",
       "129          dal80_YPEtOH    dal80           YPEtOH               1   \n",
       "130  dal82_MinimalGlucose    dal82   MinimalGlucose               3   \n",
       "131  rtg3_AmmoniumSulfate     rtg3  AmmoniumSulfate               9   \n",
       "\n",
       "     label_media  \n",
       "0              1  \n",
       "1              3  \n",
       "2             10  \n",
       "3              0  \n",
       "4              3  \n",
       "..           ...  \n",
       "127            6  \n",
       "128            4  \n",
       "129           10  \n",
       "130            4  \n",
       "131            0  \n",
       "\n",
       "[132 rows x 5 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_25687/557461149.py:26: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
      "  df_clustering = pd.concat([df_clustering, media_temp, genetics_temp], axis = 0, ignore_index=True)\n"
     ]
    }
   ],
   "source": [
    "# kmeans clustering\n",
    "from sklearn.cluster import KMeans\n",
    "est = KMeans(n_clusters=nc) # we pass two more clusters  \n",
    "est.fit(df)\n",
    "kmeans_labels = est.labels_\n",
    "df_kmeans = get_clustering_scores(df_labels['label_media'].values, df_labels['label_genetics'].values, kmeans_labels, method_label = 'kmeans')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/envs/bonobo-env/lib/python3.9/site-packages/sklearn/manifold/_spectral_embedding.py:260: UserWarning: Graph is not fully connected, spectral embedding may not work as expected.\n",
      "  warnings.warn(\n",
      "/opt/conda/envs/bonobo-env/lib/python3.9/site-packages/sklearn/manifold/_spectral_embedding.py:369: UserWarning: Failed at iteration 2 with accuracies [9.64824889e-15 3.75537898e-03 2.33486437e-02 1.31733586e-02\n",
      " 2.20617765e-02 3.26838963e-02 1.45037987e-02 1.80648872e-02\n",
      " 2.19232228e-02 5.25275355e-04 3.04992755e-05 1.11068951e-05\n",
      " 3.67001598e-07 8.86946653e-09 5.03397196e-14]\n",
      " not reaching the requested tolerance 1e-05.\n",
      "  _, diffusion_map = lobpcg(\n",
      "/opt/conda/envs/bonobo-env/lib/python3.9/site-packages/sklearn/manifold/_spectral_embedding.py:369: UserWarning: Exited at iteration 2 with accuracies \n",
      "[9.64824889e-15 3.75537898e-03 2.33486437e-02 1.31733586e-02\n",
      " 2.20617765e-02 3.26838963e-02 1.45037987e-02 1.80648872e-02\n",
      " 2.19232228e-02 5.25275355e-04 3.04992755e-05 1.11068951e-05\n",
      " 3.67001598e-07 8.86946653e-09 5.03397196e-14]\n",
      "not reaching the requested tolerance 1e-05.\n",
      "Use iteration 2 instead with accuracy \n",
      "0.010005481336880446.\n",
      "\n",
      "  _, diffusion_map = lobpcg(\n",
      "/opt/conda/envs/bonobo-env/lib/python3.9/site-packages/sklearn/manifold/_spectral_embedding.py:369: UserWarning: Exited postprocessing with accuracies \n",
      "[1.37640808e-15 3.75537898e-03 2.33486437e-02 1.31733586e-02\n",
      " 2.20617765e-02 3.26838963e-02 1.45037987e-02 1.80648872e-02\n",
      " 2.19232228e-02 5.25275411e-04 3.04843640e-05 1.11378379e-05\n",
      " 2.27001257e-08 6.32695553e-14 4.20342680e-07]\n",
      "not reaching the requested tolerance 1e-05.\n",
      "  _, diffusion_map = lobpcg(\n",
      "/tmp/ipykernel_25687/557461149.py:26: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
      "  df_clustering = pd.concat([df_clustering, media_temp, genetics_temp], axis = 0, ignore_index=True)\n"
     ]
    }
   ],
   "source": [
    "# Spectral clustering\n",
    "from sklearn.cluster import SpectralClustering\n",
    "sc = SpectralClustering(nc,  n_init=10, assign_labels='discretize')\n",
    "sc.fit_predict(df)  \n",
    "\n",
    "df_spectral = get_clustering_scores(df_labels['label_media'].values, df_labels['label_genetics'].values, sc.labels_, method_label = 'spectral')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>metric</th>\n",
       "      <th>value</th>\n",
       "      <th>check</th>\n",
       "      <th>clustering_method</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>adjusted_rand_score</td>\n",
       "      <td>0.045716</td>\n",
       "      <td>media</td>\n",
       "      <td>spectral</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>adjusted_rand_score</td>\n",
       "      <td>-0.003764</td>\n",
       "      <td>genetics</td>\n",
       "      <td>spectral</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>adjusted_mutual_info_score</td>\n",
       "      <td>0.216110</td>\n",
       "      <td>media</td>\n",
       "      <td>spectral</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>adjusted_mutual_info_score</td>\n",
       "      <td>-0.030406</td>\n",
       "      <td>genetics</td>\n",
       "      <td>spectral</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>completeness_score</td>\n",
       "      <td>0.695786</td>\n",
       "      <td>media</td>\n",
       "      <td>spectral</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>completeness_score</td>\n",
       "      <td>0.164529</td>\n",
       "      <td>genetics</td>\n",
       "      <td>spectral</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>fowlkes_mallows_score</td>\n",
       "      <td>0.304599</td>\n",
       "      <td>media</td>\n",
       "      <td>spectral</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>fowlkes_mallows_score</td>\n",
       "      <td>0.225181</td>\n",
       "      <td>genetics</td>\n",
       "      <td>spectral</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       metric     value     check clustering_method\n",
       "0         adjusted_rand_score  0.045716     media          spectral\n",
       "1         adjusted_rand_score -0.003764  genetics          spectral\n",
       "2  adjusted_mutual_info_score  0.216110     media          spectral\n",
       "3  adjusted_mutual_info_score -0.030406  genetics          spectral\n",
       "4          completeness_score  0.695786     media          spectral\n",
       "5          completeness_score  0.164529  genetics          spectral\n",
       "6       fowlkes_mallows_score  0.304599     media          spectral\n",
       "7       fowlkes_mallows_score  0.225181  genetics          spectral"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_spectral"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cluster import DBSCAN\n",
    "\n",
    "if False:\n",
    "    sparse_corr = df.T.corr()\n",
    "\n",
    "    db = DBSCAN(eps=5, min_samples=2,metric= 'precomputed' ).fit(sparse_corr)\n",
    "    labels = db.labels_\n",
    "\n",
    "    # Number of clusters in labels, ignoring noise if present.\n",
    "    n_clusters_ = len(set(labels)) - (1 if -1 in labels else 0)\n",
    "    n_noise_ = list(labels).count(-1)\n",
    "\n",
    "    df_dbscan = get_clustering_scores(df_labels['label_media'].values, df_labels['label_genetics'].values, labels, method_label = 'dbscan')\n",
    "\n",
    "    print(n_clusters_, n_noise_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_25687/557461149.py:26: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
      "  df_clustering = pd.concat([df_clustering, media_temp, genetics_temp], axis = 0, ignore_index=True)\n"
     ]
    }
   ],
   "source": [
    "# Agglomerative clustering\n",
    "from sklearn.cluster import AgglomerativeClustering\n",
    "df_ac = pd.DataFrame()\n",
    "for link in ['ward']:\n",
    "    ac = AgglomerativeClustering(n_clusters=nc, linkage=link)\n",
    "    ac.fit_predict(df)  \n",
    "\n",
    "    df_ac_temp = get_clustering_scores(df_labels['label_media'].values, df_labels['label_genetics'].values, ac.labels_, method_label = 'ac_'+link)\n",
    "    df_ac = pd.concat([df_ac, df_ac_temp], axis = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Concatenate all tables and save\n",
    "if network_name.startswith('lioness'):\n",
    "    clustering_performance = pd.concat([df_kmeans, df_ac], axis = 0)\n",
    "else:\n",
    "    clustering_performance = pd.concat([df_kmeans, df_spectral, df_ac], axis = 0)\n",
    "clustering_performance.to_csv(results_folder + 'clustering_performance.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>metric</th>\n",
       "      <th>value</th>\n",
       "      <th>check</th>\n",
       "      <th>clustering_method</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>adjusted_rand_score</td>\n",
       "      <td>0.006836</td>\n",
       "      <td>media</td>\n",
       "      <td>kmeans</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>adjusted_rand_score</td>\n",
       "      <td>0.001224</td>\n",
       "      <td>genetics</td>\n",
       "      <td>kmeans</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>adjusted_mutual_info_score</td>\n",
       "      <td>0.016657</td>\n",
       "      <td>media</td>\n",
       "      <td>kmeans</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>adjusted_mutual_info_score</td>\n",
       "      <td>0.003045</td>\n",
       "      <td>genetics</td>\n",
       "      <td>kmeans</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>completeness_score</td>\n",
       "      <td>0.454022</td>\n",
       "      <td>media</td>\n",
       "      <td>kmeans</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>completeness_score</td>\n",
       "      <td>0.440286</td>\n",
       "      <td>genetics</td>\n",
       "      <td>kmeans</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>fowlkes_mallows_score</td>\n",
       "      <td>0.271071</td>\n",
       "      <td>media</td>\n",
       "      <td>kmeans</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>fowlkes_mallows_score</td>\n",
       "      <td>0.250855</td>\n",
       "      <td>genetics</td>\n",
       "      <td>kmeans</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>adjusted_rand_score</td>\n",
       "      <td>0.006836</td>\n",
       "      <td>media</td>\n",
       "      <td>ac_ward</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>adjusted_rand_score</td>\n",
       "      <td>0.000316</td>\n",
       "      <td>genetics</td>\n",
       "      <td>ac_ward</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>adjusted_mutual_info_score</td>\n",
       "      <td>0.016657</td>\n",
       "      <td>media</td>\n",
       "      <td>ac_ward</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>adjusted_mutual_info_score</td>\n",
       "      <td>0.000797</td>\n",
       "      <td>genetics</td>\n",
       "      <td>ac_ward</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>completeness_score</td>\n",
       "      <td>0.454022</td>\n",
       "      <td>media</td>\n",
       "      <td>ac_ward</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>completeness_score</td>\n",
       "      <td>0.435273</td>\n",
       "      <td>genetics</td>\n",
       "      <td>ac_ward</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>fowlkes_mallows_score</td>\n",
       "      <td>0.271071</td>\n",
       "      <td>media</td>\n",
       "      <td>ac_ward</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>fowlkes_mallows_score</td>\n",
       "      <td>0.249461</td>\n",
       "      <td>genetics</td>\n",
       "      <td>ac_ward</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       metric     value     check clustering_method\n",
       "0         adjusted_rand_score  0.006836     media            kmeans\n",
       "1         adjusted_rand_score  0.001224  genetics            kmeans\n",
       "2  adjusted_mutual_info_score  0.016657     media            kmeans\n",
       "3  adjusted_mutual_info_score  0.003045  genetics            kmeans\n",
       "4          completeness_score  0.454022     media            kmeans\n",
       "5          completeness_score  0.440286  genetics            kmeans\n",
       "6       fowlkes_mallows_score  0.271071     media            kmeans\n",
       "7       fowlkes_mallows_score  0.250855  genetics            kmeans\n",
       "0         adjusted_rand_score  0.006836     media           ac_ward\n",
       "1         adjusted_rand_score  0.000316  genetics           ac_ward\n",
       "2  adjusted_mutual_info_score  0.016657     media           ac_ward\n",
       "3  adjusted_mutual_info_score  0.000797  genetics           ac_ward\n",
       "4          completeness_score  0.454022     media           ac_ward\n",
       "5          completeness_score  0.435273  genetics           ac_ward\n",
       "6       fowlkes_mallows_score  0.271071     media           ac_ward\n",
       "7       fowlkes_mallows_score  0.249461  genetics           ac_ward"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clustering_performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 995.875x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context('paper')\n",
    "g1 = sns.catplot(data = clustering_performance.reset_index(), \n",
    "            col = 'metric', \n",
    "            y = 'value', \n",
    "            hue = 'check',\n",
    "            x = 'clustering_method', \n",
    "            kind = 'bar', \n",
    "            aspect = 1.5,\n",
    "            height=3, \n",
    "            col_wrap = 2,\n",
    "            sharey = False, \n",
    "            hue_order = ['media', 'genetics'],\n",
    "            palette = [media_color, genetics_color], )\n",
    "\n",
    "# add title\n",
    "g1.fig.suptitle(network_name)\n",
    "plt.tight_layout()\n",
    "\n",
    "# Save figure\n",
    "g1.savefig(results_folder + 'clustering_performance.pdf', bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.18"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
